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<table width="100%"><tr><td>centiles.split(gamlss)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R:   centiles.split">
<param name="keyword" value=" Plots centile curves split by x for a GAMLSS object">
</object>


<h2>Plots centile curves split by x for a GAMLSS object</h2>


<h3>Description</h3>

<p>
This function plots centiles curves for separate ranges of the unique explanatory variable x. 
It is similar to the <code><a href="centiles.html">centiles</a></code> function but the range of x is split at a user defined values <code>xcut.point</code> into r separate ranges.
The functions also tabulates the sample percentages below each centile curve for each of the r ranges of x 
(for comparison with the model percentage given by cent)
The model should have only one explanatory variable.
</p>


<h3>Usage</h3>

<pre>
centiles.split(obj, xvar = NULL, xcut.points = NULL, n.inter = 4, 
               cent = c(0.4, 2, 10, 25, 50, 75, 90, 98, 99.6), 
               legend = FALSE, main = NULL, main.gsub = "@", 
               ylab = "y", xlab = "x", ylim = NULL, overlap = 0, 
               save = TRUE, plot = TRUE, ...)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>obj</code></td>
<td>
a fitted gamlss object from fitting a gamlss continuous distribution</td></tr>
<tr valign="top"><td><code>xvar</code></td>
<td>
the unique explanatory variable</td></tr>
<tr valign="top"><td><code>xcut.points</code></td>
<td>
the x-axis cut off points e.g. <code>c(20,30)</code>. If <code>xcut.points=NULL</code> then the <code>n.inter</code> argument is activated </td></tr>
<tr valign="top"><td><code>n.inter</code></td>
<td>
if <code>xcut.points=NULL</code> this argument gives the number of intervals in which the x-variable will be splited, with default 4 </td></tr>
<tr valign="top"><td><code>cent</code></td>
<td>
a vector with elements the % centile values for which the centile curves are to be evaluated</td></tr>
<tr valign="top"><td><code>legend</code></td>
<td>
whether a legend is required in the plots or not, the default is <code>legent=FALSE</code>  </td></tr>
<tr valign="top"><td><code>main</code></td>
<td>
the main title as character. 
If NULL the default title (shown the intervals) is shown</td></tr>
<tr valign="top"><td><code>main.gsub</code></td>
<td>
if the <code>main.gsub</code> (with default "@") appears in the <code>main</code> 
title then it is substituted with the default title.</td></tr>
<tr valign="top"><td><code>ylab</code></td>
<td>
the y-variable label</td></tr>
<tr valign="top"><td><code>xlab</code></td>
<td>
the x-variable label</td></tr>
<tr valign="top"><td><code>ylim</code></td>
<td>
the range of the y-variable axis</td></tr>
<tr valign="top"><td><code>overlap</code></td>
<td>
how much overlapping in the <code>xvar</code> intervals. Default value is <code>overlap=0</code> for non overlapping intervals</td></tr>
<tr valign="top"><td><code>save</code></td>
<td>
whether to save the sample percentages or not with default equal to <code>TRUE</code>. 
In this case the functions produce a matrix giving the sample percentages for each interval </td></tr>
<tr valign="top"><td><code>plot</code></td>
<td>
whether to plot the centles. This option is usefull if the sample statistics only are to be used</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
for extra arguments</td></tr>
</table>

<h3>Details</h3>




<h3>Value</h3>

<p>
Centile plots are produced and the sample centiles below each centile curve for each of the r ranges of x can be saved into a matrix.</p>

<h3>Warning</h3>

<p>
This function is appropriate when only one continuous explanatory variable is fitted in the model
</p>


<h3>Note</h3>




<h3>Author(s)</h3>

<p>
Mikis Stasinopoulos, <a href="mailto:d.stasinopoulos@londonmet.ac.uk">d.stasinopoulos@londonmet.ac.uk</a>, Bob Rigby <a href="mailto:r.rigby@londonmet.ac.uk">r.rigby@londonmet.ac.uk</a>, with contributions from Elaine Borghie
</p>


<h3>References</h3>

<p>
Rigby, R. A. and  Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), 
<EM>Appl. Statist.</EM>, <B>54</B>, part 3, pp 507-554.
</p>
<p>
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2003) Instructions on how to use the GAMLSS package in R.
Accompanying documentation in the current GAMLSS  help files, (see also  <a href="http://www.gamlss.com/">http://www.gamlss.com/</a>).
</p>
<p>
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R.
<EM>Journal of Statistical Software</EM>, Vol. <B>23</B>, Issue 7, Dec 2007, <a href="http://www.jstatsoft.org/v23/i07">http://www.jstatsoft.org/v23/i07</a>.
</p>


<h3>See Also</h3>

<p>
<code><a href="gamlss.html">gamlss</a></code>  <code><a href="centiles.html">centiles</a></code>,   <code><a href="centiles.com.html">centiles.com</a></code>
</p>


<h3>Examples</h3>

<pre>
data(abdom)
h&lt;-gamlss(y~cs(x,df=3), sigma.formula=~cs(x,1), family=BCT, data=abdom) 
mout &lt;- centiles.split(h,xvar=abdom$x)
mout
rm(h,mout)
</pre>



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